{"id":"W4414463003","doi":"10.1109/icscds65426.2025.11167691","title":"Privacy-Centric and Explainable AI Frameworks: Combining Edge Analytics, DAG-based Systems, and GANs for Pandemic Preparedness and Healthcare Innovation","year":2025,"lang":"en","type":"article","venue":"","topic":"Privacy-Preserving Technologies in Data","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"PotashCorp (Canada)","funders":"","keywords":"Scalability; Preparedness; Big data; Health care; Enhanced Data Rates for GSM Evolution; Pandemic; Coronavirus disease 2019 (COVID-19)","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001542391,0.0004540923,0.0003500641,0.0004722729,0.0004141428,0.001322293,0.00100582,0.0005966802,0.002705895],"category_scores_gemma":[0.004110666,0.000223354,0.0006120349,0.0007200276,0.0008986053,0.002894915,0.001711947,0.001594887,0.0003640467],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009976175,"about_ca_system_score_gemma":0.001248133,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002838671,"about_ca_topic_score_gemma":0.004269167,"domain_scores_codex":[0.9994044,0.0002601574,0.00002909339,0.0001213583,0.0001144356,0.0000704954],"domain_scores_gemma":[0.9986225,0.0006687199,0.0001220133,0.0003505793,0.0001680942,0.0000680055],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0002787648,0.000135276,0.004786174,0.0002322191,0.0001283603,0.0003716258,0.0003980424,0.4557402,0.00754652,0.2574765,0.007862971,0.2650432],"study_design_scores_gemma":[0.000006967407,0.00002827888,0.000286198,0.00001424475,0.00001458275,0.00004927167,0.0000419715,0.9041678,0.002074747,0.08985001,0.003455235,0.00001061566],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02016398,0.0002900629,0.9723864,0.001824923,0.00009001545,0.00005195366,0.000210244,0.0006944782,0.004287927],"genre_scores_gemma":[0.7832265,0.0006368444,0.2109111,0.0005367874,0.0001124465,0.0000910557,0.0004195292,0.0001008123,0.003964936],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002838671,"threshold_uncertainty_score":0.009052157,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.039068734390298,"score_gpt":0.3226965588757387,"score_spread":0.2836278244854407,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}